Please wait a minute...
Submit  |   Chinese  | 
Advanced Search
   Home  |  Online Now  |  Current Issue  |  Focus  |  Archive  |  For Authors  |  Journal Information   Open Access  
Submit  |   Chinese  | 
Engineering    2017, Vol. 3 Issue (5) : 753 -759
Research |
Methane Emissions from Grazing Holstein-Friesian Heifers at Different Ages Estimated Using the Sulfur Hexafluoride Tracer Technique
Steven J. Morrison1,Judith McBride1,Alan W. Gordon2,Alastair R. G. Wylie2,Tianhai Yan1()
1. Agri-Food and Biosciences Institute, Hillsborough, County Down BT26 6DR, UK
2. Agri-Food and Biosciences Institute, Belfast BT9 5PX, UK

Although the effect of animal and diet factors on enteric methane (CH4) emissions from confined cattle has been extensively examined, less data is available regarding CH4 emissions from grazing young cattle. A study was undertaken to evaluate the effect of the physiological state of Holstein-Friesian heifers on their enteric CH4 emissions while grazing a perennial ryegrass sward. Two experiments were conducted: Experiment 1 ran from May 2011 for 11 weeks and Experiment 2 ran from August 2011 for 10 weeks. In each experiment, Holstein-Friesian heifers were divided into three treatment groups (12 animals/group) consisting of calves, yearling heifers, and in-calf heifers (average ages: 8.5, 14.5, and 20.5 months, respectively). Methane emissions were estimated for each animal in the final week of each experiment using the sulfur hexafluoride tracer technique. Dry matter (DM) intake was estimated using the calculated metabolizable energy (ME) requirement divided by the ME concentration in the grazed grass. As expected, live weight increased with increasing animal age (P<0.001); however, there was no difference in live weight gain among the three groups in Experiment 1, although in Experiment 2, this variable decreased with increasing animal age (P<0.001). In Experiment 1, yearling heifers had the highest CH4 emissions (g·d−1) and in-calf heifers produced more than calves (P<0.001). When expressed as CH4 emissions per unit of live weight, DM intake, and gross energy (GE) intake, yearling heifers had higher emission rates than calves and in-calf heifers (P<0.001). However, the effects on CH4 emissions were different in Experiment 2, in which CH4 emissions (g·d−1) increased linearly with increasing animal age (P<0.001), although the difference between yearling and in-calf heifers was not significant. The CH4/live weight ratio was lower in in-calf heifers than in the other two groups (P<0.001), while CH4 energy output as a proportion of GE intake was lower in calves than in yearling and in-calf heifers (P<0.05). All data were then pooled and used to develop prediction equations for CH4 emissions. All relationships are significant (P<0.001), with R2 values ranging from 0.630 to 0.682. These models indicate that CH4 emissions could be increased by 0.252 g·d−1 with an increase of 1 kg live weight or by 14.9 g·d−1 with an increase of 1 kg·d−1 of DM intake; or, the CH4 energy output could be increased by 0.046 MJ·d−1 with an increase of 1 MJ·d−1 of GE intake. These results provide an alternative approach for estimating CH4 emissions from grazing dairy heifers when actual CH4 emission data are not available.

Keywords Methane emission      Grazing dairy heifer      Prediction      Sulfur hexafluoride tracer technique     
Corresponding Authors: Tianhai Yan   
Just Accepted Date: 17 May 2017   Online First Date: 17 August 2017    Issue Date: 08 November 2017
E-mail this article
E-mail Alert
Articles by authors
Steven J. Morrison
Judith McBride
Alan W. Gordon
Alastair R. G. Wylie
Tianhai Yan
Cite this article:   
Steven J. Morrison,Judith McBride,Alan W. Gordon, et al. Methane Emissions from Grazing Holstein-Friesian Heifers at Different Ages Estimated Using the Sulfur Hexafluoride Tracer Technique[J]. Engineering, 2017, 3(5): 753 -759 .
URL:     OR
1   European Environment Agency.EEA greenhouse gas—Data viewer [Internet]. Copenhagen: European Environment Agency. [updated 2016 Dec 6; cited 2017 Jan 20]. Available from:
2   Food and Agriculture Organization.Greenhouse gas emissions from the dairy sector—A life cycle assessment [Internet]. Copenhagen: Food and Agriculture Organization. 2010 [cited 2017 Jan 20]. Available from:
3   Ellis JL, Kebreab E, Odongo NE, McBride BW, Okine EK, France J. Prediction of methane production from dairy and beef cattle. J Dairy Sci 2007;90(7):3456–66
doi: 10.3168/jds.2006-675
4   Yan T, Mayne CS, Gordon FG, Porter MG, Agnew RE, Patterson DC, et al.Mitigation of enteric methane emissions through improving efficiency of energy utilization and productivity in lactating dairy cows. J Dairy Sci 2010;93(6):2630–8
doi: 10.3168/jds.2009-2929
5   Jiao HP, Yan T, Wills DA, Carson AF, McDowell DA. Development of prediction models for quantification of total methane emission from enteric fermentation of young Holstein cattle at various ages. Agric Ecosyst Environ 2014;183:160–6
doi: 10.1016/j.agee.2013.11.004
6   Johnson K, Huyler M, Westberg H, Lamb B, Zimmerman P. Measurement of methane emissions from ruminant livestock using a SF6 tracer technique. Environ Sci Technol 1994;28:359–62
doi: 10.1021/es00051a025
7   Grainger C, Clarke T, McGinn SM, Auldist MJ, Beauchemin KA, Hannah MC, et al.Methane emissions from dairy cows measured using the sulfur hexafluoride (SF6) tracer and chamber techniques. J Dairy Sci 2007;90(6):2755–66
doi: 10.3168/jds.2006-697
8   Muñoz C, Yan T, Wills DA, Murray S, Gordon AW. Comparison of the sulfur hexafluoride tracer and respiration chamber techniques for estimating methane emissions and correction for rectum methane output from dairy cows. J Dairy Sci 2012;95(6):3139–48
doi: 10.3168/jds.2011-4298
9   Dale AJ, Mayne CS, Laidlaw AS, Ferris CP. Effect of altering the grazing interval on growth and utilization of grass herbage and performance of dairy cows under rotational grazing. Grass Forage Sci 2008;63(2):257–69
doi: 10.1111/j.1365-2494.2008.00631.x
10   Park RS, Agnew RE, Gordon FJ, Steen RWJ. The use of near infrared reflectance spectroscopy (NIRS) on undried samples of grass silage to predict chemical composition and digestibility parameters. Anim Feed Sci Technol 1998;72(1–2):155–67
doi: 10.1016/S0377-8401(97)00175-2
11   Porter MG. Comparison of sample preparation methods for the determination of the gross energy concentration of fresh silage. Anim Feed Sci Technol 1992;37(3–4):207–8
doi: 10.1016/0377-8401(92)90004-P
12   Cushnahan A, Gordon FG. The effects of grass preservation on intake, apparent digestibility and rumen degradation characteristics. Anim Sci J 1995;60(3):429–38
doi: 10.1017/S1357729800013308
13   Agricultural and Food Research Council.Energy and protein requirements of ruminants. Report. Wallingford: CAB International; 1993.
14   Eggleston HS, Buendia L, Miwa K, Ngara T, Tanabe K, editors. IPCC guidelines for national greenhouse gas inventories. Copenhagen: Intergovernmental Panel on Climate Change (IPCC); 2006.
15   Baggott SL, Cardenas L, Downes M, Garnett E, Jackson J, Li Y, et al.Greenhouse gas inventories for England, Scotland, Wales and Northern Ireland: 1990–2004. Report. Didcot: AEA Technology plc.; 2006 Nov. Report No.: AEAT/ENV/R/2318.
16   Crompton LA, Mills JA, Kliam KE, Reynolds CK. Effects of feeding milled rapeseed on methane emission and milk fatty acid composition in lactating dairy cows. Adv Anim Biosci 2011;2:75.
17   Yan T, Agnew RE, Gordon FJ, Porter MG. Prediction of methane energy output in dairy and beef cattle offered grass silage-based diets. Livest Prod Sci 2000;64(2–3):253–63
doi: 10.1016/S0301-6226(99)00145-1
18   Jiao HP, Dale AJ, Carson AF, Murray S, Gordon AW, Ferris CP. Effect of concentrate feed level on methane emissions from grazing dairy cows. J Dairy Sci 2014;97(11):7043–53
doi: 10.3168/jds.2014-7979
19   Cavanagh A, McNaughton L, Clark H, Greaves C, Gowan JM, Pinares-Patino C, et al.Methane emissions from grazing Jersey × Friesian dairy cows in mid lactation. Aust J Exp Agric 2008;48(2):230–3
doi: 10.1071/EA07277
20   Boland TM, Quinlan C, Pierce KM, Lynch MB, Kenny DA, Kelly AK, et al.The effect of pasture pregrazing herbage mass on methane emissions, ruminal fermentation, and average daily gain of grazing beef heifers. J Anim Sci 2013;91(8):3867–74
doi: 10.2527/jas.2013-5900
21   Deighton MH, Williams SRO, Lassey KR, Hannah MC, Boland TM, Eckard RJ, et al.Temperature, but not submersion or orientation, influences the rate of sulphur hexafluoride release from permeation tubes used for estimation of ruminant methane emissions. Anim Feed Sci Technol 2014;194:71–80
doi: 10.1016/j.anifeedsci.2014.05.006
22   Williams SRO, Moate PJ, Hannah MC, Ribaux BE, Wales WJ, Eckard RJ. Background matters with the SF6 tracer method for estimating enteric methane emissions from dairy cows: A critical evaluation of the SF6 procedure. Anim Feed Sci Technol 2011;170(3–4):265–76
doi: 10.1016/j.anifeedsci.2011.08.013
23   Johnson KA, Johnson DE. Methane emissions from cattle. J Anim Sci 1995;73(8):2483–92
doi: 10.2527/1995.7382483x
24   Bannink A, van Schijndel MW, Dijkstra J. A model of enteric fermentation in dairy cows to estimate methane emission for the Dutch National Inventory Report using the IPCC Tier 3 approach. Anim Feed Sci Technol 2011;166– 7:603–18
doi: 10.1016/j.anifeedsci.2011.04.043
25   Boadi DA, Wittenberg KM, Kennedy AD. Validation of the sulphur hexafluoride (SF6) tracer gas technique for measurement of methane and carbon dioxide production by cattle. Can J Anim Sci 2002;82(2):125–31
doi: 10.4141/A01-054
26   Moe PW, Tyrell HF. Methane production in dairy cows. J Dairy Sci 1979;62(10):1583–6
doi: 10.3168/jds.S0022-0302(79)83465-7
27   Blaxter KL, Clapperton JL. Prediction of the amount of methane produced by ruminants. Br J Nutr 1965;19(4):511–22
doi: 10.1079/BJN19650046
28   McCaughey WP, Wittenberg K, Corrigan D. Methane production by steers on pasture. Can J Anim Sci 1997;77(3):519–24
doi: 10.4141/A96-137
29   Hart KJ, Martin PG, Foley PA, Kenny DA, Boland M. Effect of sward dry matter digestibility on methane production, ruminal fermentation, and microbial populations of zero-grazed beef cattle. J Anim Sci 2009;87(10):3342–50
doi: 10.2527/jas.2009-1786
30   Johnson DE, Ward GM, Ramsey JJ. Livestock methane: Current emissions and mitigation potential. In: Kornegay ET, editor Nutrient management of food animals to enhance and protect the environment. New York: CRC Press Inc.; 1996. p. 219–33.
31   Yan T, Mayne CS, Porter MG. Effects of dietary and animal factors on methane production in dairy cows offered grass silage-based diets. In: Proceedings of the 2nd International Conference on Greenhouse Gases and Animimal Agriculture; 2005 Sep 20–24; Zurich, Switzerland. Amsterdam: Elsevier; 2006. p. 131–4
doi: 10.1016/j.ics.2006.02.024
32   Mills JA, Kebreab E, Yates CM, Crompton LA, Cammell SB, Dhanoa MS, et al.Alternative approaches to predicting methane emissions from dairy cows. J Anim Sci 2003;81(12):3141–50
doi: 10.2527/2003.81123141x
33   Zhao YG, O’Connell NE, Yan T. Prediction of enteric methane emissions from sheep offered fresh perennial ryegrass (Lolium perenne) using data measured in indirect open-circuit respiration chambers. J Anim Sci 2016;94(6):2425–35
doi: 10.2527/jas.2016-0334
34   Carson AF, Dawson LER, McCoy MA, Kilpatrick DJ, Gordon FJ. Effects of rearing regime on body size, reproductive performance and milk production during the first lactation in high genetic merit dairy herd replacements. Anim Sci 2002;74(3):553–65
doi: 10.1017/S1357729800052711
[1] He Zhuang, Liping Feng, Chao Wen, Qiyuan Peng, Qizhi Tang. High-Speed Railway Train Timetable Conflict Prediction Based on Fuzzy Temporal Knowledge Reasoning[J]. Engineering, 2016, 2(3): 366 -373 .
Copyright © 2015 Higher Education Press & Engineering Sciences Press, All Rights Reserved.
Today's visits ;Accumulated visits . 京ICP备11030251号-2